The new severe acute respiratory syndrome-coronavirus 2 is reported to affect the nervous system. Among the reports of the various neurological manifestations, there are a few documented specific processes to explain the neurological signs. We report a para-infectious encephalitis patient with clinical, laboratory, and imaging findings during evolution and convalescence phase of coronavirus infection. This comprehensive overview can illuminate the natural history of similar cases. As the two previously reported cases of encephalitis associated with this virus were not widely discussed regarding the treatment, we share our successful approach and add some recommendations about this new and scarce entity.

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Multiple sclerosis (MS) is the most prevalent central nervous system demyelinating disease. There are known risk factors for MS. However, there is uncertainty in its protective factors. Few studies have demonstrated that some chronic infections may have protective effects on this disease. We carried this study to investigate the relation between Helicobacter pylori (HP) infection and the prevalence and severity of MS. In this case-control study, 163 MS patients and 150 sex- and age- matched controls were included. Blood samples for IgG and IgM anti HP antibodies were collected from all individuals. Also, the Expanded Disability Status Scale (EDSS) was used to evaluate the MS patients. Suitable statistical analysis was applied. A Significant difference was observed in seropositivity between these two groups (P<0.001) but no significant difference was seen in seropositivity between conventional and opticospinal MS (P=0.522). No significant difference was observed in seropositivity among ages (P=0.075) and between genders (P=0.204). A significant difference was seen in EDSS value between seropositive and seronegative patients (P=0.017). We concluded that patients with HP infection had lower incidence of multiple sclerosis and MS patients with HP infection showed lower neurologic complications, which can demonstrate that HP infection may have a protective influence on MS pathogenesis.

BackgroundThere are many similarities with regard to contributing cytokines in patients with psoriasis and osteoporosis. A theory of probable relationship between these two entities has been proposed but there is no concordant consensus. The aim of this study was to evaluate bone mineral density (BMD) in patients with psoriasis.Method and materialsThis cross-sectional study of BMD was conducted with 64 eligible patients with psoriasis who were referred to the dermatology clinic of Razi hospital in Tehran, Iran in between 2011 and 2012.ResultsThe mean T score of femoral neck was –1.17 and –0.49 in men and women, respectively, which was statistically significant (p = .047). The mean T score of the lumbar spine was –0.93 and –0.30 in men and women, respectively, but not statistically significant (p = .058). In total except with the exclusion of the study site (femur or lumbar), men and women did not have a statistically significant difference with regard to osteoporosis or osteopenia in BMD (p = .114). The Pearson correlation coefficient demonstrated a moderate inverse relationship between age and T score of the femoral neck and lumbar spine (r = –0.419 and –.406, respectively), which was statistically significant (p = .001). Although there was no statistically significant relationship between the Psoriasis Area and Severity Index (PASI) and T scores of the femoral neck (p = .596), a positive and weak correlation was observed between the PASI and T scores for the lumbar spine, which was statistically significant (r = 0.269; p = .03).ConclusionPatients with psoriasis had decreased bone density, which was more significant in men. Prevalence of osteoporosis showed no statistically significant difference when compared with the healthy population in Iran.

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Background Choosing a safe disease modifying therapy during the COVID-19 pandemic is challenging. This case series study was conducted to determine the incidence rate and the course of Covid-19 infection in MS/NMOSD patients treated with Rituximab. Methods In this study, we designed a web-based questionnaire. Baseline information such as patient- reported walking disability, total number of Rituximab infusions received, delayed injections, occurrence of any relapse, and the use of corticosteroids during the pandemic were collected. Also, information regarding the Covid-19 pandemic such as adherence to self-isolation, any recent exposure to an infected individual and the presence of suggestive symptoms were collected. In case of positive test results, patients were grouped into 2 categories; mild to moderate and seriously ill and outcomes were evaluated as favorable (improved/ discharged) and unfavorable (expired). Results Two hundred fifty-eight patients with Multiple Sclerosis were enrolled in this study, 9 of the subjects (3.4%) were confirmed positive for Covid-19, five of which required hospitalizations (55.5%), two patients required ICU admission (22.2%) and 2 two patients died (22.2%). None of these patients ever mentioned using corticosteroids during the pandemic. In comparison to MS patients who were not receiving disease modifying therapy (DMT), our study indicated a higher incidence of Covid-19 infection, higher ratio of serious illness and a higher fatality ratio. Conclusions Rituximab seems not to be safe enough during the pandemic.

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A neuro-fuzzy based model is proposed in this paper for estimating the Lyapunov exponents of an unknown dynamical system according solely to a set of observations. Several approaches have been presented in recent years; most of them using the approximation of both the function of the trajectory of observations and the partial derivatives, to yield the Jacobian matrix of the function. The Jacobian matrix is then employed in the Jacobian-based methods that extract the Lyapunov exponents by QR-decomposition. While the accurate estimation of Lyapunov exponents has been sought, most of the related papers mainly focus on the accuracy of the trajectory approximation. In this paper, an Adaptive Neuro-Fuzzy Inference System is presented and stated to be an efficient tool for such a purpose. Structural parameters of the proposed model as the embedding dimension and the delay time are calculated by the Takens theorem and autocorrelation function, respectively. Model validation is performed by cross approximate entropy. Then, the promising performance of the proposed model as an accurate estimation of the Lyapunov exponents and its robustness to the measurement noise are finally evaluated.